Model comparison
Gemini 2.5 Flash-Lite vs Qwen3 32B
Qwen3 32B is the stronger model overall, scoring 39.2 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 7.0× less per token, which makes it the better buy when Qwen3 32B's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 20 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 5 categories and Qwen3 32B in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where Qwen3 32B leads 43.8 to 33.3.
- The biggest single-benchmark swing is Fiction.LiveBench: 47.2% for Gemini 2.5 Flash-Lite and 74.2% for Qwen3 32B.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 131K.
- Qwen3 32B has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash-Lite | Qwen3 32B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 37.0 | 39.2 |
| Released | 2025-06-17 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 131K |
| Max output | 66K | 16K |
| Input $ / M tokens | $0.10 | $0.70 |
| Output $ / M tokens | $0.40 | $2.80 |
| Results tracked | 33 | 26 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Too close to call
Gemini 2.5 Flash-Lite: 38.5 (#173), Qwen3 32B: 37.7 (#190)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| LMArena Coding | 1373 | 1358 |
| Aider Polyglot | — | 40% |
| SciCode | — | 35.4% |
| WeirdML | 35.2% | — |
| ALE-Bench | 325.9 | — |
Agentic & Tool Use Qwen3 32B leads
Gemini 2.5 Flash-Lite: 28.0 (#96), Qwen3 32B: 32.6 (#62)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | 48.7% |
Reasoning Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 22.2 (#205), Qwen3 32B: 20.2 (#241)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| Kagi LLM Benchmark | 40.5% | 54.9% |
| LMArena Hard Prompts | 1377 | 1334 |
| DTBench | 62.8% | 67.5% |
| LMCA | 18.1% | 17.3% |
| Epoch Capabilities Index | 133.94 | 138.51 |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 5% |
Math Qwen3 32B leads
Gemini 2.5 Flash-Lite: 38.0 (#144), Qwen3 32B: 39.7 (#99)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| LMArena Math | 1373 | 1399 |
| OTIS Mock AIME 2024-2025 | — | 66.9% |
| Omni-MATH | 48% | — |
Knowledge Qwen3 32B leads
Gemini 2.5 Flash-Lite: 32.5 (#210), Qwen3 32B: 40.0 (#125)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| Vectara Hallucination Rate | 3.3% | 5.9% |
| LMArena Expert | 1373 | 1362 |
| GPQA Diamond | — | 65.7% |
| MMLU-Pro | 53.7% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal Not comparable
Gemini 2.5 Flash-Lite: 29.1 (#114), Qwen3 32B: —
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| LMArena Vision | 1198 | — |
| VPCT | 30% | — |
Multilingual Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 49.3 (#134), Qwen3 32B: 45.6 (#167)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1369 | 1317 |
| LMArena Chinese | 1404 | 1357 |
| LMArena German | 1389 | 1341 |
| LMArena Russian | 1373 | 1311 |
| LMArena French | 1388 | — |
| LMArena Japanese | 1359 | — |
| LMArena Korean | 1360 | — |
| LMArena Spanish | 1396 | — |
Instruction Following Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 70.0 (#168), Qwen3 32B: 68.9 (#179)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1367 | 1305 |
| IFEval | 81% | — |
Long Context Qwen3 32B leads
Gemini 2.5 Flash-Lite: 33.3 (#262), Qwen3 32B: 43.8 (#87)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| Fiction.LiveBench | 47.2% | 74.2% |
| LMArena Longer Query | 1373 | 1327 |
Writing & Preference Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 56.8 (#135), Qwen3 32B: 52.9 (#163)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3 32B |
|---|---|---|
| LMArena Text | 1379 | 1340 |
| LMArena Creative Writing | 1367 | 1297 |
| LMArena Multi-Turn | 1366 | 1331 |
| WildBench | 81.8% | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than Qwen3 32B?
Qwen3 32B is the stronger model overall, scoring 39.2 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 7.0× less per token, which makes it the better buy when Qwen3 32B's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or Qwen3 32B?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.
Is Gemini 2.5 Flash-Lite or Qwen3 32B better for coding?
They score almost the same on coding (38.5 vs 37.7); test both on your own repository before choosing.
Which has the bigger context window?
Gemini 2.5 Flash-Lite does, with 1.05M tokens against 131K.
How many benchmarks do Gemini 2.5 Flash-Lite and Qwen3 32B share?
20 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and Qwen3 32B has 26.